Medical Biotechnology

Activity type

Discipline biotecnologiche comuni

SSD

BIO/09

Year

N/D

Semester

N/D

CFU

4

Hours distribution

32 classroom hours

Lecturers

GIANLUCA DI FLUMERI
DARIO ROSSI

Activity type

Discipline medico-chirurgiche e riproduzione umana

SSD

MED/18

Year

N/D

Semester

N/D

CFU

1

Hours distribution

8 classroom hours

Lecturers

GIANLUCA DI FLUMERI

Activity type

Discipline medico-chirurgiche e riproduzione umana

SSD

MED/50

Year

N/D

Semester

N/D

CFU

3

Hours distribution

24 classroom hours

Lecturers

GIANLUCA BORGHINI
FABIO BABILONI

Activity type

Attività formative affini o integrative

SSD

ING-INF/06

Year

N/D

Semester

N/D

CFU

1

Hours distribution

8 classroom hours

Lecturers

GIANLUCA BORGHINI

Objectives:
By the end of the course, students will be expected to know the physical and technological principles behind the most widely used neuroimaging techniques in clinical and industrial settings, the precautions and characteristics for their use and choice, the fundamentals of statistics for validating results, principles of programming for computational analyses, how to define an experimental protocol while also considering Ethics and Data Protection (GDPR) aspects.

Specific objectives:
1. Knowledge and understanding
Students should acquire knowledge of the physical principles, and electronic and technological characteristics of the main neuroimaging techniques. In addition, they should be able to interpret and discuss results from experimental protocols following the use of specific technologies and methodologies.

2. Ability to apply knowledge and understanding
Students will be expected to acquire the ability to apply their acquired knowledge to describe the most relevant relationships between the particular choice of neuroimaging technology, experimental protocol and statistical tests, and purposes of its use and application.

3. Autonomy of judgment
The lessons will be interactive. The teacher will ask continuous questions to students to stimulate the critical sense and integrate their previous knowledge. These questions will also serve to induce students to establish links between the notions acquired during the lessons in an integrated and critical view of Electronic Bioengineering.

4. Communication skills
The ability of students to present the topics covered in the program with appropriate terms and speeches will be carefully evaluated. They will have to be able to describe the topics covered in an orderly and organically way, managing both to give a detailed view of the technologies and methodologies covered in class and an overall relationship and differences between them.

5. Learning skills
Students will be taught to critically integrate and memorize the most important notions derived from multiple sources of study, including those received in class and those read in the recommended texts and resources available on the WEB and in scientific literature.

No prerequisites are needed.

Module: MODULE 1
Core curriculum.
This program will be carried out during the 2 year 1 semester of the CdS with schedule of the lessons published on the website of the CdS in the section dedicated to the timetable of the lessons.
The topics are intended to be carried out in temporal succession as reported in the rest of the document.
Cellular Physiology and Biophysics 3 CFU
• What physiology studies. Concept of homeostasis. Body fluids.
• Physiology of blood cells - The general functions of the blood. - The constituents of blood: plasma, erythrocytes, leukocytes, platelets. Hemostasis.
• The cell as basic unit: electrical parameters of the cell membrane and equivalent circuits; resting potential; action potential. - Voltage-gated ion channels. - Biophysical methods for the study of membrane electrical events.
• Neurotransmitters
• Electrical synapses: structure and function. -
• Chemical synapses. Spontaneous and evoked transmitter release. Synaptic potential; spatial and temporal summation. The neuromuscular junction.
• Membrane receptors: Ionotropic receptor families: structural analogies and functional peculiarities. - Metabotropic receptor families: structural analogies and functional diversity. - Second messenger systems and signal transduction. Synaptic activity and cognitive and mnemonic processes.
• Muscle physiology 1 CFU
The muscle: structure and function of the various types of muscle. - The contraction of skeletal, smooth and cardiac muscle.
• Ortho and parasympathetic autonomic nervous system.
Respiratory and cardiocirculatory centers 2 CFU
• Physiology of the heart and blood circulation
Laws of fluid mechanics applied to blood circulation. Arterial pressure and peripheral resistance. The heart: physiological aspects of the myocardium; the cardiac cycle. Cardiac output and venous return. Excitation of the myocardium and impulse conduction; nerve control mechanisms. - The electrocardiogram. - Microcirculation and lymphatic system: Exchanges between blood and tissues. - Control of blood flow and arterial pressure. Methods of measuring blood pressure.
• Physiology of respiration 2 CFU
Respiration: functional structure of the lung. - Pulmonary pressures and ventilation; lung volumes - Mechanical properties of the lung. - The pulmonary circulation. - Gas exchanges - Transport of respiratory gases. - Breathing control.


Module: MODULE 2
N/D
Module: MODULE 3
Objectives
To provide an exhaustive and comprehensive overview of modern neuroscience approaches for real-time measurement of human mental states during consumption and work activities, as well as in rehabilitative and clinical practices. To understand the foundations of technologies that aim to place humans at the center of interaction with next-generation machines and devices (e.g., aircrafts, autonomous vehicles).

Program
Introduction: Neuroscience and Neurotechnology
1. The Basics of Thought: Fundamentals of Nerve Cell Physiology
- Excitable membrane and resting potential
- Active and passive transport mechanisms, gated ion channels
- Generation and propagation of action potentials
- Synaptic transmission
- Central and Peripheral Nervous Systems
- Study of attention, memory, emotion, and executive control functions

2. Measuring Human Brain Activity: The Central Nervous System and Techniques for Measuring Related Electrical Activities
- Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging (fMRI)
- Positron Emission Tomography (PET)
- Near-Infrared Spectroscopy (fNIRS)
- Magnetoencephalography (MEG)
- Electroencephalography (EEG)
- Application examples

3. Decoding Brain Activity in Real-Time: How and Why - Brain-Computer Interaction (BCI) and Machine Learning Models
- Brain signal decoding and definition of Brain-Computer Interface (BCI)
- Introduction to linear machine learning models
- Introduction to nonlinear machine learning models
- Clinical and industrial application examples

4. Measuring Emotions: The Autonomic Nervous System and Techniques for Measuring Related Activities
- Nature and analysis of the Electrocardiographic (ECG) signal
- Evaluation and correlates of the ECG signal
- Nature and analysis of the Galvanic Skin Response (GSR) signal
- Evaluation and correlates of the GSR signal
- Nature and analysis of eye movement signals: EOG and Eye Tracker
- Evaluation and correlates of eye movement signals

5. Knowing How to Evaluate Brain Measurement Results: Definition of Experimental Protocols and Statistical Validation
- Basic experimental protocols
- Within and Between experimental protocols
- Control conditions and preparation of the experimental protocol
- Validation of results and introduction to statistical analysis
- Considerations on ethics and data protection (GDPR)

6. Applied Neurosciences in Industrial and Clinical Contexts
- Evaluation of mental states in aeronautical contexts
- Neuroplasticity mechanisms during training
- Auditory-cognitive neuroscience in relation to cochlear implant use
- Evaluation of characteristic patterns in different populations of patients with hearing disabilities
- Evaluation of stress in Air Traffic Controllers
- Evaluation of mental states in the automotive context
- Passive BCI and adaptive automation to improve Human-Machine/Cobot interaction in operational and industrial contexts
- Evaluation of mental states in clinical contexts
- Neuroergonomics: definition and application examples
- Neuroaesthetics: definition and application examples in real contexts

7. Measuring Consumer Choices Through Neuroscience: Neuromarketing
- Cerebral foundations of higher functions (attention, perception, emotion, learning, memory, decision-making processes)
- Brain imaging methodologies in humans and the use of game theory to study brain activity in social interactions associated with risks and benefits; use of brain imaging methodologies (with particular reference to electroencephalographic and nuclear magnetic resonance techniques) to assess the impact of advertising communications on human brain activity
- Experimental designs of Neuroeconomics and Neuromarketing for studying the effects of advertising content on attention, memory, and emotions
- Experimental designs of Neuroeconomics and Neuromarketing for studying the effects of political information on voter choices


Module: MODULE 4
Objectives
To provide an exhaustive and comprehensive overview of modern neuroscience approaches for real-time measurement of human mental states during consumption and work activities, as well as in rehabilitative and clinical practices. To understand the foundations of technologies that aim to place humans at the center of interaction with next-generation machines and devices (e.g., aircrafts, autonomous vehicles).

Program
Introduction: Neuroscience and Neurotechnology
1. The Basics of Thought: Fundamentals of Nerve Cell Physiology
- Excitable membrane and resting potential
- Active and passive transport mechanisms, gated ion channels
- Generation and propagation of action potentials
- Synaptic transmission
- Central and Peripheral Nervous Systems
- Study of attention, memory, emotion, and executive control functions

2. Measuring Human Brain Activity: The Central Nervous System and Techniques for Measuring Related Electrical Activities
- Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging (fMRI)
- Positron Emission Tomography (PET)
- Near-Infrared Spectroscopy (fNIRS)
- Magnetoencephalography (MEG)
- Electroencephalography (EEG)
- Application examples

3. Decoding Brain Activity in Real-Time: How and Why - Brain-Computer Interaction (BCI) and Machine Learning Models
- Brain signal decoding and definition of Brain-Computer Interface (BCI)
- Introduction to linear machine learning models
- Introduction to nonlinear machine learning models
- Clinical and industrial application examples

4. Measuring Emotions: The Autonomic Nervous System and Techniques for Measuring Related Activities
- Nature and analysis of the Electrocardiographic (ECG) signal
- Evaluation and correlates of the ECG signal
- Nature and analysis of the Galvanic Skin Response (GSR) signal
- Evaluation and correlates of the GSR signal
- Nature and analysis of eye movement signals: EOG and Eye Tracker
- Evaluation and correlates of eye movement signals

5. Knowing How to Evaluate Brain Measurement Results: Definition of Experimental Protocols and Statistical Validation
- Basic experimental protocols
- Within and Between experimental protocols
- Control conditions and preparation of the experimental protocol
- Validation of results and introduction to statistical analysis
- Considerations on ethics and data protection (GDPR)

6. Applied Neurosciences in Industrial and Clinical Contexts
- Evaluation of mental states in aeronautical contexts
- Neuroplasticity mechanisms during training
- Auditory-cognitive neuroscience in relation to cochlear implant use
- Evaluation of characteristic patterns in different populations of patients with hearing disabilities
- Evaluation of stress in Air Traffic Controllers
- Evaluation of mental states in the automotive context
- Passive BCI and adaptive automation to improve Human-Machine/Cobot interaction in operational and industrial contexts
- Evaluation of mental states in clinical contexts
- Neuroergonomics: definition and application examples
- Neuroaesthetics: definition and application examples in real contexts

7. Measuring Consumer Choices Through Neuroscience: Neuromarketing
- Cerebral foundations of higher functions (attention, perception, emotion, learning, memory, decision-making processes)
- Brain imaging methodologies in humans and the use of game theory to study brain activity in social interactions associated with risks and benefits; use of brain imaging methodologies (with particular reference to electroencephalographic and nuclear magnetic resonance techniques) to assess the impact of advertising communications on human brain activity
- Experimental designs of Neuroeconomics and Neuromarketing for studying the effects of advertising content on attention, memory, and emotions
- Experimental designs of Neuroeconomics and Neuromarketing for studying the effects of political information on voter choices

Module: MODULE 1
For the examination of the exam, we suggest a theoretical deepening already from the beginning of the course attendance.
For the purpose of consultation and in-depth study, the recommended books are:
Guyton and Hall: Human Physiology. EdiSES, 2000
Berne and Levy: Physiology. Ambrosiana Publishing, 2000
Baldissera: Physiology and Medical Biophysics. Poletto Publisher
E. Kandel: Principles of Neural Science. McGraw-Hill Companies, 2000 (for consultation in the library)
E. Kandel: Principles of Neural Science. McGraw-Hill Companies, 2000 (for consultation in the library)
Other teaching aids for Human Physiology I


Module: MODULE 2
N/D
Module: MODULE 3
Suggested textbooks

Aaron J. Newman, Research Methods for Cognitive Neuroscience, SAGE

Borghini et al., Industrial Neuroscience in Aviation, Biosystems & Biorobotics (BIOSYSROB, volume 7)

Vecchiato et al. Neuroelectrical Brain Imaging Tools for the Study of the Efficacy of TV Advertising Stimuli and their Application to Neuromarketing, Biosystems & Biorobotics (BIOSYSROB, volume 3)

Other resources

Slides with the lessons and exercises for the preparation of the exam (electronic archive indicated by the lecturer).


Module: MODULE 4
Suggested textbooks

Aaron J. Newman, Research Methods for Cognitive Neuroscience, SAGE

Borghini et al., Industrial Neuroscience in Aviation, Biosystems & Biorobotics (BIOSYSROB, volume 7)

Vecchiato et al. Neuroelectrical Brain Imaging Tools for the Study of the Efficacy of TV Advertising Stimuli and their Application to Neuromarketing, Biosystems & Biorobotics (BIOSYSROB, volume 3)

Other resources

Slides with the lessons and exercises for the preparation of the exam (electronic archive indicated by the lecturer).

Module: MODULE 1
N/D
Module: MODULE 2
N/D
Module: MODULE 3
N/D
Module: MODULE 4
N/D

The teaching consists of lectures with the students, with some specific seminars and sessions dedicated to computational analyses. The lessons are all interactive, so the teacher stimulates the students with questions to which they, by virtue of the courses already followed, can give an answer. This allows the teacher to highlight the links between the current course and some previous courses, whose notions play a key role in the understanding of what is presented in the class. The continuous remanding to concepts of other courses must get the student to study the proposed subject not only with the aim of passing the final exam, but wants to highlight a multidisciplinary study, to which the student has to be educated and that is absolutely required for a master's degree student, now almost at the end of his training. The student will find on the e-learning platform teaching material (exam program, recommended texts, links) useful for the preparation of the exam. It is understood that all material is a guide to the exam topics, but they can never absolutely replace the recommended texts.

Attendance to the course is not mandatory.

The evaluation methods of the Teaching are characterized by exam sessions set in the scheduled sessions.
The exam consists of a written task with both multiple-choice and open-ended questions and verbal interview on the topics of the Teaching, followed by a clarification on the evaluation criteria at the request of the student or student.
The exam aims to certify the student's knowledge of physic principles, electronic and operating characteristics of most common neuroimaging techniques, processing of neurophysiological signals, principles of programming for computational analyses, validation of results in terms of statistics, definition of experimental protocols, examples of clinical and industrial applications, and management of ethical and privacy aspects of collected data. The topics presented must be treated with proper language.
The elements examined for evaluation purposes are listed below: (1) the knowledge of the subject in all the areas included in the teaching program; (2) the use of a proper language; (3) the ability to reasoning; (4) the logical articulation of the wording; and (5) the integration of skills demonstrated in the response to exam questions. The verbal and written nature of the exam will allow correcting the individual evaluation of the student’s elaborate according to "item analysis" techniques. This procedure will allow not to penalize areas of the answer that will be insufficient in most of the students involved a certain exam appeal. Furthermore, the evaluation of the single student will be conducted comparatively, to guarantee equanimity and recognize the individual merits in the allocation of grades.
In the evaluation process, we will also consider (1) the ability of the student to manage the time agreed to supply the answers in a concise but exhaustive manner and (2) link the key concepts in a logical and coherent way.

Module: MODULE 1
N/D
Module: MODULE 2
N/D
Module: MODULE 3
N/D
Module: MODULE 4
N/D

Module: MODULE 1
N/D
Module: MODULE 2
N/D
Module: MODULE 3
N/D
Module: MODULE 4
N/D